Importing libraries¶

In [1]:
# install face_recognition package

import subprocess
import sys

# -- uncomment --

subprocess.check_call([sys.executable, "-m", "pip", "install", "face_recognition"])
!pip install face_recognition

Requirement already satisfied: face_recognition in /usr/local/lib/python3.10/dist-packages (1.3.0)
Requirement already satisfied: face-recognition-models>=0.3.0 in /usr/local/lib/python3.10/dist-packages (from face_recognition) (0.3.0)
Requirement already satisfied: Click>=6.0 in /usr/local/lib/python3.10/dist-packages (from face_recognition) (8.1.7)
Requirement already satisfied: dlib>=19.7 in /usr/local/lib/python3.10/dist-packages (from face_recognition) (19.24.2)
Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from face_recognition) (1.23.5)
Requirement already satisfied: Pillow in /usr/local/lib/python3.10/dist-packages (from face_recognition) (9.4.0)
In [2]:
# import libraries
import requests
import zipfile
import os
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

# image stuff
import face_recognition
from PIL import Image, ImageDraw, ImageFont, ImageFilter, ImageOps, ImageEnhance
from google.colab.patches import cv2_imshow
In [3]:
from google.colab import drive
drive.mount('/content/drive')

Mounted at /content/drive

remove an irrelevant value¶

files.remove('.ipynb_checkpoints')

Checking my Image¶

In [4]:
# Define the URL of the image file
image_file = "/content/drive/MyDrive/CSV Uploads/Eric_Mayo.jpg"

# open an image
image = Image.open(image_file)

# Get the original size of the image
width, height = image.size
print("Original image size:", width, height)

# Resize the image to half its original size
new_size = (int(width/2), int(height/2))
resized_image = image.resize(new_size)

new_width, new_height = resized_image.size
print("Resized image size:", new_width, new_height)

# Display the image in the Colab notebook
display(resized_image)

# Get the new size of the image

Original image size: 4032 3024
Resized image size: 2016 1512

Loop Over the Excel file¶

In [5]:
match_file = pd.read_excel("/content/drive/MyDrive/CSV Uploads/FinalMatchSourceTarget.xlsx")
match_file.head()
Out[5]:
match_id source_image name target_image expected_match
0 100 Bingyu_Li.jpg Bingyu_Li Bingyu_Li_aged.jpg match
1 101 Whitney_Joyce_Isbell.jpg Whitney_Joyce_Isbell Whitney_Joyce_Isbell_aged.jpg match
2 102 Qian_Chen.jpg Qian_Chen Qian_Chen_aged.jpg match
3 103 Hanshuai_Shi.jpg Hanshuai_Shi Hanshuai_Shi_aged.jpg match
4 104 Ruochen_Bao.jpg Ruochen_Bao Ruochen_Bao_aged.jpg match

Comparing Current Self to Aged¶

In [6]:
# 1. load two faces using load_image_file
face_file1 = "/content/drive/MyDrive/CSV Uploads/Eric_Mayo.jpg"
face_file2 = "/content/drive/MyDrive/CSV Uploads/Eric_Mayo_aged.jpg"
image1 = face_recognition.load_image_file(face_file1)
image2 = face_recognition.load_image_file(face_file2)
In [7]:
# 2. Compare the face_encodings similarity using face_distance
img1_encoding = face_recognition.face_encodings(image1)[0]
img2_encoding = face_recognition.face_encodings(image2)[0]

# Calculate the distance between the faces
face_distance = face_recognition.face_distance([img1_encoding], img2_encoding)

# Normalize the distance to get the similarity score
similarity = 1 - face_distance[0]

# Print the similarity score
print("The two faces are '{:.2f}%' similar".format(similarity*100))

The two faces are '62.09%' similar
In [8]:
# 3. is it a match?
face_matches = face_recognition.compare_faces([img1_encoding], img2_encoding)

# Print the result
if face_matches[0]:
    print("The two faces match")
else:
    print("The two faces do not match")

The two faces match
In [9]:
# 4. Display Side by Side

# Open the two image files
image1 = Image.open(face_file1)
image2 = Image.open(face_file2)

# Get the dimensions of the images
width1, height1 = image1.size
width2, height2 = image2.size

# Create a new blank image with a size equal to the sum of the widths of the two images
new_image = Image.new("RGB", (width1 + width2, max(height1, height2)))

# Paste the first image onto the new image at position (0, 0)
new_image.paste(image1, (0, 0))

# Paste the second image onto the new image at position (width1, 0)
new_image.paste(image2, (width1, 0))

# Add text to the image
text = '{} % MATCH'.format(int(similarity*100))
font = ImageFont.truetype("/content/drive/MyDrive/CSV Uploads/Roboto-Medium.ttf", size=48)
draw = ImageDraw.Draw(new_image)
text_width, text_height = draw.textsize(text, font)
left = 900
top =  100
right = left + text_width
bottom = top + text_height
draw.rectangle(((left, top), (right, bottom)), fill=(255, 255, 255, 128))
draw.text((left, top), text, font=font, fill=(0, 0, 0, 255))

# Save the new image to a file
new_image.save("merged_image.jpg")

# Display the new image
new_image.show()

<ipython-input-9-59ba36c6dbef>:24: DeprecationWarning: textsize is deprecated and will be removed in Pillow 10 (2023-07-01). Use textbbox or textlength instead.
  text_width, text_height = draw.textsize(text, font)

Autoamation¶

In [10]:
dir_name = 'images'
def list_jpeg_files(directory):
    """List all JPEG files in the specified directory."""
    jpeg_files = [file for file in os.listdir(directory) if file.lower().endswith(('.jpeg', '.jpg'))]
    return jpeg_files


# Replace 'your_directory_path' with the path to the directory you want to search
directory_path = '/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students'
jpeg_files = list_jpeg_files(directory_path)

print("JPEG files in the directory:", jpeg_files)

JPEG files in the directory: ['Angela_Waszkiewicz.jpg', 'Whitney_Joyce_Isbell.jpg', 'Manling_Shi_aged.jpg', 'Joseph_Macon_Barker_aged.jpg', 'Yue_Zhou.jpg', 'Jodie_Elizabeth_Brine.jpg', 'Meryl_Criswell_Kaduboski.jpg', 'Boyu_Zheng_aged.jpg', 'Tianyi_Yin_aged.jpg', 'Qian_Chen.jpg', 'Yuchen_Qin_aged.jpg', 'Shuzhe_Wang_aged.jpg', 'Christopher_Craig_Kenney_aged.jpg', 'Tianyu_Cui.jpg', 'Jacob_Philip_Rockaway.jpg', 'Kendall_Ashley_Hilson.jpg', 'Marcus_Cole_cooper.jpg', 'Yilin_Wang.jpg', 'Helen_Kidane_Haile.jpg', 'Edward_Cheongjoun_Hyun.jpg', 'Bintong_Zhai.jpg', 'Shanay_Nimish_Sonawala_aged.jpg', 'Alfredo_Enrique_Suarez_aged_aged.jpg', 'Anoush_U_Shah_aged.jpg', 'Benjamin_Pyung-Hwa_Aikens_aged.jpg', 'Logan_Trujillo_aged.jpg', 'Michelle_Monica_Saikali.jpg', 'Amanda_Renner_Gild.jpg', 'Cheuk_Yui_Marcus_Chan.jpg', 'Garhett_William_Sessions.jpg', 'Haopeng_Liu_aged.jpg', 'Lu_Xing.jpg', 'Natalie_Weiner.jpg', 'Christopher_David_Koontz.jpg', 'Jodie_Elizabeth_Brine_aged.jpg', 'Shenghao_Yang.jpg', 'Zihe_Liu_aged.jpg', 'Shenzhe_Lian_aged.jpg', 'Kyle_John_Wiblishauser_aged.jpg', 'Kaitlyn_R_Vickers.jpg', 'Millie_C_Garrett_aged.jpg', 'Ruochen_Bao_aged.jpg', 'Zaul_Alexander_Perez_aged.jpg', 'Chioke_K_Bellamy.jpg', 'Alfredo_Enrique_Suarez_aged.jpg', 'Reid_Powers_Walker.jpg', 'Jiaming_Zhang_aged.jpg', 'Hanshuai_Shi.jpg', 'Jiahao_Ma.jpg', 'Boyu_Zheng.jpg', 'Ruochen_Bao.jpg', 'Cole_Ritchey_aged.jpg', 'Skylour_Sebastian_Winakur.jpg', 'Ryan_Marek_Smith_aged.jpg', 'Guangxin_Bao_aged.jpg', 'Jax_Francis_Revfi.jpg', 'Estefani_Santiago_Gatica.jpg', 'Harve_E_Criqui_aged.jpg', 'Anne_M_Perry_aged.jpg', 'Hangfei_Lyu.jpg', 'Xiyan_Huang_aged.jpg', 'Millie_C_Garrett.jpg', 'Hanshuai_Shi_aged.jpg', 'Andrew_Dubois_aged.jpg', 'Manling_Shi.jpg', 'Elizabeth_G_Higgins.jpg', 'Wei_Tan_aged.jpg', 'Dillon_Hunter_Aryeh_aged.jpg', 'Nicolson_Charles_Panos_aged.jpg', 'Evan_Anderson_Gilbert.jpg', 'Chengzhan_Shen_aged.jpg', 'Xiyue_Yu_aged.jpg', 'Edward_Cheongjoun_Hyun_aged.jpg', 'Jacob_Philip_Rockaway_aged.jpg', 'Emmanuel_Thomas_George_Skora.jpg', 'Mengyao_Liu.jpg', 'Zihe_Liu.jpg', 'Eric_Mayo_aged.jpg', 'Raleigh_Coolidge_Conway_aged.jpg', 'Marcus_Cole_cooper_aged.jpg', 'Natalie_Weiner_aged.jpg', 'Zaul_Alexander_Perez.jpg', 'Jackson_R_Harper_aged.jpg', 'Hangfei_Lyu_aged.jpg', 'Andrew_Lloyd_Loftis.jpg', 'Savannah_Kayla_Littlejohn.jpg', 'Bingnan_Lei_aged.jpg', 'Jax_Francis_Revfi_aged.jpg', 'Niklas_Jozef_Baldis.jpg', 'Xiaoyang_Zheng.jpg', 'Xiyan_Huang.jpg', 'Haopeng_Liu.jpg', 'Andrea_Chen_aged.jpg', 'Khushi_Arya.jpg', 'Patrick_Ryan_Weimaker.jpg', 'Wentong_Guo_aged.jpg', 'Xingyu_Wan.jpg', 'Jeremy_Brian_Nurding.jpg', 'Khushi_Arya_aged.jpg', 'Yiming_Xu_aged.jpg', 'Sebastian_Andres_Lopez-Ibanez_aged.jpg', 'Joseph_Macon_Barker.jpg', 'Jiaming_Zhang.jpg', 'Jiahua_Wu_aged.jpg', 'Logan_Trujillo.jpg', 'Evan_Anderson_Gilbert_aged.jpg', 'Kyle_John_Wiblishauser.jpg', 'Mary_Martha_Milcoff.jpg', 'Cole_Ritchey.jpg', 'Hewei_Shen_aged.jpg', 'John_William_Null_aged.jpg', 'Anthony_X_Ayala_aged.jpg', 'Luying_Huang_aged.jpg', 'Allen_Gail_Smith_aged.jpg', 'Alicia_Rand_Bodoia_aged.jpg', 'George_Basil_Economus.jpg', 'Qian_Chen_aged.jpg', 'Max_Koontz.jpg', 'Bintong_Zhai_aged.jpg', 'Latham_Alexander_Weaver_aged.jpg', 'Angela_Waszkiewicz_aged.jpg', 'Nathanael_Hunter_Kraus_aged.jpg', 'Anoush_U_Shah.jpg', 'Lu_Xing_aged.jpg', 'Chengzhan_Shen.jpg', 'Yuchen_Qin.jpg', 'Xiaoyang_Zheng_aged.jpg', 'Amanda_Renner_Gild_aged.jpg', 'Mary_Michele_Troise_aged.jpg', 'Shenzhe_Lian.jpg', 'Jiahao_Ma_aged.jpg', 'Jennifer_Ontiveros-Olivas.jpg', 'Sebastian_Andres_Lopez-Ibanez.jpg', 'Jeremy_Brian_Nurding_aged.jpg', 'Allen_Gail_Smith.jpg', 'Shenger_Zhou_aged.jpg', 'Shenghao_Yang_aged.jpg', 'Jackson_R_Harper.jpg', 'Estefani_Santiago_Gatica_aged.jpg', 'Kaushik_Rajaram_aged.jpg', 'Andrew_Lloyd_Loftis_aged.jpg', 'Guangxin_Bao.jpg', 'Nathalie_Lisa_Friedman_aged.jpg', 'Siyu_Lin_aged.jpg', 'Alicia_Rand_Bodoia.jpg', 'Kayla_Marie_Williams_aged.jpg', 'Yanghua_Zhang_aged.jpg', 'Bryce_Charles_Drynan.jpg', 'Anne_M_Perry.jpg', 'Boyan_Wei_aged.jpg', 'Bingnan_Lei.jpg', 'Qin_Miao_aged.jpg', 'Savannah_Kayla_Littlejohn_aged.jpg', 'Tianyi_Yin.jpg', 'Songlin_Liu.jpg', 'Helen_Kidane_Haile_aged.jpg', 'Nicholas_J_Sundberg_aged.jpg', 'Luying_Huang.jpg', 'Tianyi_Chen_aged.jpg', 'Michelle_Monica_Saikali_aged.jpg', 'Michael_Jason_Vejsiri.jpg', 'Kayla_Marie_Williams.jpg', 'Meryl_Criswell_Kaduboski_aged.jpg', 'Xiyue_Yu.jpg', 'Latham_Alexander_Weaver.jpg', 'Kaushik_Rajaram.jpg', 'Yutong_Ouyang.jpg', 'Garhett_William_Sessions_aged.jpg', 'Andrea_Chen.jpg', 'Jiahua_Wu.jpg', 'Cheuk_Yui_Marcus_Chan_aged.jpg', 'Xiaoyu_Zong.jpg', 'Dillon_Hunter_Aryeh.jpg', 'Siyu_Lin.jpg', 'Whitney_Joyce_Isbell_aged.jpg', 'Andrew_Dubois.jpg', 'Daniel_Madden_Sheedy_aged.jpg', 'Mary_Michele_Troise.jpg', 'Shenger_Zhou.jpg', 'Skylour_Sebastian_Winakur_aged.jpg', 'Nathanael_Hunter_Kraus.jpg', 'Tianyu_Cui_aged.jpg', 'Jiacheng_Wang_aged.jpg', 'Dongqiao_Tang_aged.jpg', 'Michael_Jason_Vejsiri_aged.jpg', 'Max_Koontz_aged.jpg', 'Tianyi_Chen.jpg', 'Yiming_Xu.jpg', 'Patrick_Ryan_Weimaker_aged.jpg', 'Raleigh_Coolidge_Conway.jpg', 'Shuzhe_Wang.jpg', 'Lauren_Elizabeth_Johnson.jpg', 'George_Basil_Economus_aged.jpg', 'Hewei_Shen.jpg', 'Reid_Powers_Walker_aged.jpg', 'Wentong_Guo.jpg', 'Xiaoyu_Zong_aged.jpg', 'Samantha_O_Brien_aged.jpg', 'Wei_Tan.jpg', 'Jennifer_Ontiveros-Olivas_aged.jpg', 'Joseph_Miller_Hirsch_aged.jpg', 'Trinity_Nicole_Elliott_aged.jpg', 'Bryce_Charles_Drynan_aged.jpg', 'Benjamin_Pyung-Hwa_Aikens.jpg', 'Jiacheng_Wang.jpg', 'Ryan_Marek_Smith.jpg', 'Harve_E_Criqui.jpg', 'Emmanuel_Thomas_George_Skora_aged.jpg', 'Meghan_O_Malley_aged.jpg', 'Yutong_Ouyang_aged.jpg', 'Joseph_Miller_Hirsch.jpg', 'Kendall_Ashley_Hilson_aged.jpg', 'Qin_Miao.jpg', 'Xiaoya_Luo.jpg', 'Samantha_O_Brien.jpg', 'Christopher_David_Koontz_aged.jpg', 'Yanghua_Zhang.jpg', 'Nicolson_Charles_Panos.jpg', 'Niklas_Jozef_Baldis_aged.jpg', 'Meghan_O_Malley.jpg', 'Bingyu_Li_aged.jpg', 'Yilin_Wang_aged.jpg', 'Anthony_X_Ayala.jpg', 'Christopher_Craig_Kenney.jpg', 'Xingyu_Wan_aged.jpg', 'Alfredo_Enrique_Suarez.jpg', 'Xiaoya_Luo_aged.jpg', 'Bingyu_Li.jpg', 'Nicholas_J_Sundberg.jpg', 'Kaamil_Farooqi_aged.jpg', 'Kaitlyn_R_Vickers_aged.jpg', 'Trinity_Nicole_Elliott.jpg', 'Lauren_Elizabeth_Johnson_aged.jpg', 'Yue_Zhou_aged.jpg', 'John_William_Null.jpg', 'Songlin_Liu_aged.jpg', 'Elizabeth_G_Higgins_aged.jpg', 'Eric_Mayo.jpg', 'Kaamil_Farooqi.jpg', 'Chioke_K_Bellamy_aged.jpg', 'Daniel_Madden_Sheedy.jpg', 'Dongqiao_Tang.jpg', 'Boyan_Wei.jpg', 'Mengyao_Liu_aged.jpg', 'Shanay_Nimish_Sonawala.jpg', 'Nathalie_Lisa_Friedman.jpg', 'Mary_Martha_Milcoff_aged.jpg']
In [20]:
def face_load_source():
  face_dict = {}

  for file in jpeg_files:
    try:
      img_file = "/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/{}".format(file)
      print(img_file)
      # load the face
      _t = face_recognition.load_image_file(img_file)
      # generate the encoding
      _x = face_recognition.face_encodings(_t)[0]
      face_dict[img_file] = _x
    except IndexError:
        _x = 0
        face_dict[img_file] = _x
        print("No face was found in the image.")

  return face_dict

Encodings¶

In [21]:
face_source_encodings = face_load_source()

/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Angela_Waszkiewicz.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Whitney_Joyce_Isbell.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Manling_Shi_aged.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Joseph_Macon_Barker_aged.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Yue_Zhou.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Jodie_Elizabeth_Brine.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Meryl_Criswell_Kaduboski.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Boyu_Zheng_aged.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Tianyi_Yin_aged.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Qian_Chen.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Yuchen_Qin_aged.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Shuzhe_Wang_aged.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Christopher_Craig_Kenney_aged.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Tianyu_Cui.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Jacob_Philip_Rockaway.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Kendall_Ashley_Hilson.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Marcus_Cole_cooper.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Yilin_Wang.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Helen_Kidane_Haile.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Edward_Cheongjoun_Hyun.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Bintong_Zhai.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Shanay_Nimish_Sonawala_aged.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Alfredo_Enrique_Suarez_aged_aged.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Anoush_U_Shah_aged.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Benjamin_Pyung-Hwa_Aikens_aged.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Logan_Trujillo_aged.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Michelle_Monica_Saikali.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Amanda_Renner_Gild.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Cheuk_Yui_Marcus_Chan.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Garhett_William_Sessions.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Haopeng_Liu_aged.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Lu_Xing.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Natalie_Weiner.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Christopher_David_Koontz.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Jodie_Elizabeth_Brine_aged.jpg
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/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Kaitlyn_R_Vickers.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Millie_C_Garrett_aged.jpg
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/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Chioke_K_Bellamy.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Alfredo_Enrique_Suarez_aged.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Reid_Powers_Walker.jpg
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/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Nathalie_Lisa_Friedman.jpg
/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Mary_Martha_Milcoff_aged.jpg

Saving to Pickle¶

This was actually my 13th reason because my pickle didn't work when re-running everything because I forgot to make a heatmap when I first created the notebook.

In [22]:
import pickle
# Save the face encodings to a file
with open('encodings.pickle', 'wb') as f:
    pickle.dump(face_source_encodings, f)
In [23]:
# Load the encodings pickle if you lose it
import pickle
with open("encodings.pickle", "rb") as f:
    face_source_encodings = pickle.load(f)
In [24]:
# convert to dataframe
data_items = list(face_source_encodings.items())

# Create DataFrame
face_df = pd.DataFrame(data_items, columns=['image', 'encoding'])
face_df.head()
Out[24]:
image encoding
0 /content/drive/MyDrive/CSV Uploads/msba_studen... [-0.04089708626270294, 0.07306627184152603, 0....
1 /content/drive/MyDrive/CSV Uploads/msba_studen... [-0.09973771870136261, 0.07061269134283066, 0....
2 /content/drive/MyDrive/CSV Uploads/msba_studen... [-0.12598378956317902, 0.15065625309944153, 0....
3 /content/drive/MyDrive/CSV Uploads/msba_studen... [-0.11492722481489182, 0.1706923544406891, 0.0...
4 /content/drive/MyDrive/CSV Uploads/msba_studen... [-0.08087983727455139, 0.053938671946525574, 0...
In [25]:
def compare_faces_df2(sourceFile, targetFile):
  similarity = 0
  try:
    index1 = '/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/' + str(sourceFile)
    index2 = '/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/' + str(targetFile)
    encoding1 = face_source_encodings[index1]
    encoding2 = face_source_encodings[index2]
    distance = face_recognition.face_distance([encoding1], encoding2)[0]
    similarity = 1-distance
  except Exception as e:
    print(f"An error occurred: {e}")

  return similarity
In [26]:
match_file2 = pd.read_excel("/content/drive/MyDrive/CSV Uploads/FinalMatchSourceTarget.xlsx")

# idk why but we gotta replace '.jpeg' with '.jpg'
match_file2['source_image'] = match_file2['source_image'].str.replace('.jpeg','.jpg')
match_file2['target_image'] = match_file2['target_image'].str.replace('.jpeg','.jpg')
match_file2 = match_file2[match_file2['source_image'] != '_aged.jpg']
match_file2 = match_file2[match_file2['target_image'] != '_aged.jpg']

match_file2['source_image'] = match_file2['source_image'].str.strip()
match_file2['target_image'] = match_file2['target_image'].str.strip()

<ipython-input-26-a502db01e682>:4: FutureWarning: The default value of regex will change from True to False in a future version.
  match_file2['source_image'] = match_file2['source_image'].str.replace('.jpeg','.jpg')
<ipython-input-26-a502db01e682>:5: FutureWarning: The default value of regex will change from True to False in a future version.
  match_file2['target_image'] = match_file2['target_image'].str.replace('.jpeg','.jpg')
In [27]:
match_file2.head()
Out[27]:
match_id source_image name target_image expected_match
0 100 Bingyu_Li.jpg Bingyu_Li Bingyu_Li_aged.jpg match
1 101 Whitney_Joyce_Isbell.jpg Whitney_Joyce_Isbell Whitney_Joyce_Isbell_aged.jpg match
2 102 Qian_Chen.jpg Qian_Chen Qian_Chen_aged.jpg match
3 103 Hanshuai_Shi.jpg Hanshuai_Shi Hanshuai_Shi_aged.jpg match
4 104 Ruochen_Bao.jpg Ruochen_Bao Ruochen_Bao_aged.jpg match
In [28]:
match_file2['match_similarity'] = match_file2.apply(lambda row: compare_faces_df2(row['source_image'], row['target_image']), axis=1)

An error occurred: '/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Jash_Sanjaybhai_Vachhani.jpg'
An error occurred: '/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Quinn_Poole.jpg'
An error occurred: '/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Quinn_Poole_aged.jpg'
An error occurred: '/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/Jash_Sanjaybhai_Vachhani.jpg'
An error occurred: '/content/drive/MyDrive/CSV Uploads/msba_students_2024/content/SAM/2024_students/.ipynb_checkpoints'

Predicted Matches¶

In [29]:
match_file2['predicted_match'] = np.where(match_file2['match_similarity'] > 0.5, 'match','no match')
match_file2
Out[29]:
match_id source_image name target_image expected_match match_similarity predicted_match
0 100 Bingyu_Li.jpg Bingyu_Li Bingyu_Li_aged.jpg match 0.629741 match
1 101 Whitney_Joyce_Isbell.jpg Whitney_Joyce_Isbell Whitney_Joyce_Isbell_aged.jpg match 0.562203 match
2 102 Qian_Chen.jpg Qian_Chen Qian_Chen_aged.jpg match 0.559150 match
3 103 Hanshuai_Shi.jpg Hanshuai_Shi Hanshuai_Shi_aged.jpg match 0.591559 match
4 104 Ruochen_Bao.jpg Ruochen_Bao Ruochen_Bao_aged.jpg match 0.296038 no match
... ... ... ... ... ... ... ...
171 271 Yutong_Ouyang.jpg NaN Max_Koontz_aged.jpg no match 0.080805 no match
172 272 Andrea_Chen.jpg NaN Joseph_Macon_Barker_aged.jpg no match 0.056572 no match
173 273 Xiyan_Huang.jpg NaN Kayla_Marie_Williams_aged.jpg no match 0.174988 no match
174 274 Angela_Waszkiewicz.jpg NaN Chengzhan_Shen_aged.jpg no match 0.142100 no match
175 275 Chioke_K_Bellamy.jpg NaN Yuchen_Qin_aged.jpg no match 0.017787 no match

174 rows × 7 columns

Confusion Matrix & Scores¶

In [30]:
from sklearn.metrics import confusion_matrix, accuracy_score, precision_score, recall_score

# Calculate confusion matrix
matrix = confusion_matrix(match_file2['expected_match'],
                          match_file2['predicted_match'],
                          labels=["match", "no match"])

print(matrix)

[[110  15]
 [  2  47]]
In [31]:
# Calculate confusion matrix
y_true = match_file2['expected_match']
y_pred = match_file2['predicted_match']
labels = ["match", "no match"]
matrix = confusion_matrix(y_true, y_pred, labels=labels)

# Calculate Accuracy, Precision and Recall
accuracy = accuracy_score(y_true, y_pred)
precision = precision_score(y_true, y_pred, pos_label="match")
recall = recall_score(y_true, y_pred, pos_label="match")

print("Accuracy:", accuracy)
print("Precision:", precision)
print("Recall:", recall)

Accuracy: 0.9022988505747126
Precision: 0.9821428571428571
Recall: 0.88
In [32]:
# Plotting using seaborn
plt.figure(figsize=(8, 6))
sns.heatmap(matrix, annot=True, fmt="d", xticklabels=labels, yticklabels=labels, cmap="Blues")
plt.title("Confusion Matrix")
plt.ylabel('Actual')
plt.xlabel('Predicted')
plt.show()